1. Field of the Invention
This invention relates generally to property value estimation and more particularly to using feature distances between a target property and comparables to estimate the target property value.
2. Description of the Related Art
In various real estate related businesses, it is known to estimate for the fair market value of a property at a point in time based on the observed sales amounts of similar properties in the same geographic market. This may be referred to as estimation based upon comparable properties, or comparable sales.
Conventional processes in this area are carried out in several ways. One technique is performed by human appraisers who look at records of property sales, generally by ZIP code, and select a set of properties that are believed to be similar. They then apply their judgment to adjust the value of the observed sales by the set of observed characteristics of the sale (square footage, yard, etc.) and then present these sales and adjustments to define a range of likely values.
A second approach uses automated appraisal systems that define study groups based upon jurisdictionally provided boundaries, property features and observed sales records. Regression is applied to estimate the change to a prior appraisal amount over the study group and that percentage is applied equally to all homes in the study group.
Still another technique uses automated appraisal tools that perform regression based on property characteristics, and weight that prediction with some number of recent comparable sales based on either ZIP code adjacency or by using a GIS to define concentric circles to restrict the sales records used.
The first method is not automated and is reliant upon various subjective factors as well as the experience of the appraiser. The second relies on the accuracy of the prior assessment, as well as the provided boundaries, and does not generate customized value estimates for each property. The third implements overly simple models of housing valuation, such as dollars per square foot, and can be computationally expensive when run on large datasets.
What is needed is a computationally efficient appraisal technique that accommodates calculation with large datasets, that diminishes reliance upon the accuracy of prior assessments, and that accommodates customized value estimates.